Machine learning-based mining of new associations in acupuncture-related diseases , genes and drugs

Machine learning-based mining of new associations in acupuncture-related diseases, genes and drugs WEI Xing, XIE Jing, JIANG Xiu-lin, YE Feng, ZHANG De-cheng, CHEN You-chun, ZHU Wen-jie (Bengbu Medical College Public Basic Courses School, Bengbu 233030, Anhui Province, China) [Abstract]Objective To mine the new associations in acupuncture-related diseases, genes and drugs. Methods A support vector machine (SVM)-based machine learning algorithm was proposed and different association networks for acupuncture-related diseases, genes and drugs were established by identifying the diseases, genes and drugs with dictionaries and mining their associations. Results A total of 296 acupuncture-related diseases, 51 genes and 278 drugs were identified, and 704 associations were mined in 27 diseases, 13 genes and 135 drugs. Three association networks were established, which discovered a total of 262 new associations in acupuncture related diseases, genes and drugs. Conclusion New associations are detected in acupuncture-related diseases, genes and drugs, which can thus provide certain new ideas for studying the precision treatment of diseases by acupuncture. [Key words]Acupuncture; Disease; Gene; Drug; SVM; Association network;Data mining;Text mining